from __future__ import annotations from typing import TYPE_CHECKING, Literal from pydantic import BaseModel, ConfigDict, Field from faster_whisper_server import utils if TYPE_CHECKING: from faster_whisper.transcribe import Segment, TranscriptionInfo, Word from faster_whisper_server.core import Transcription # https://platform.openai.com/docs/api-reference/audio/json-object class TranscriptionJsonResponse(BaseModel): text: str @classmethod def from_segments(cls, segments: list[Segment]) -> TranscriptionJsonResponse: return cls(text=utils.segments_text(segments)) @classmethod def from_transcription(cls, transcription: Transcription) -> TranscriptionJsonResponse: return cls(text=transcription.text) class WordObject(BaseModel): start: float end: float word: str probability: float @classmethod def from_word(cls, word: Word) -> WordObject: return cls( start=word.start, end=word.end, word=word.word, probability=word.probability, ) class SegmentObject(BaseModel): id: int seek: int start: float end: float text: str tokens: list[int] temperature: float avg_logprob: float compression_ratio: float no_speech_prob: float @classmethod def from_segment(cls, segment: Segment) -> SegmentObject: return cls( id=segment.id, seek=segment.seek, start=segment.start, end=segment.end, text=segment.text, tokens=segment.tokens, temperature=segment.temperature, avg_logprob=segment.avg_logprob, compression_ratio=segment.compression_ratio, no_speech_prob=segment.no_speech_prob, ) # https://platform.openai.com/docs/api-reference/audio/verbose-json-object class TranscriptionVerboseJsonResponse(BaseModel): task: str = "transcribe" language: str duration: float text: str words: list[WordObject] segments: list[SegmentObject] @classmethod def from_segment(cls, segment: Segment, transcription_info: TranscriptionInfo) -> TranscriptionVerboseJsonResponse: return cls( language=transcription_info.language, duration=segment.end - segment.start, text=segment.text, words=([WordObject.from_word(word) for word in segment.words] if isinstance(segment.words, list) else []), segments=[SegmentObject.from_segment(segment)], ) @classmethod def from_segments( cls, segments: list[Segment], transcription_info: TranscriptionInfo ) -> TranscriptionVerboseJsonResponse: return cls( language=transcription_info.language, duration=transcription_info.duration, text=utils.segments_text(segments), segments=[SegmentObject.from_segment(segment) for segment in segments], words=[WordObject.from_word(word) for word in utils.words_from_segments(segments)], ) @classmethod def from_transcription(cls, transcription: Transcription) -> TranscriptionVerboseJsonResponse: return cls( language="english", # FIX: hardcoded duration=transcription.duration, text=transcription.text, words=[ WordObject( start=word.start, end=word.end, word=word.text, probability=word.probability, ) for word in transcription.words ], segments=[], # FIX: hardcoded ) class ModelObject(BaseModel): id: str """The model identifier, which can be referenced in the API endpoints.""" created: int """The Unix timestamp (in seconds) when the model was created.""" object_: Literal["model"] = Field(serialization_alias="object") """The object type, which is always "model".""" owned_by: str """The organization that owns the model.""" model_config = ConfigDict( populate_by_name=True, json_schema_extra={ "examples": [ { "id": "Systran/faster-whisper-large-v3", "created": 1700732060, "object": "model", "owned_by": "Systran", }, { "id": "Systran/faster-distil-whisper-large-v3", "created": 1711378296, "object": "model", "owned_by": "Systran", }, { "id": "bofenghuang/whisper-large-v2-cv11-french-ct2", "created": 1687968011, "object": "model", "owned_by": "bofenghuang", }, ] }, )